Google Ads
Real Estate
India
Live Campaign Rescue

Live Campaign Rescue - 4x Lead Surge and 56% CPL Reduction in 9 Days for CREDAI Pune Metro Real Estate Expo.

Client: CREDAI Pune MetroIndustry: Real EstateServices: Google Ads · Performance MaxMarket: Pune · IndiaIntervention Window: 9 DaysCampaign Type: Live rescue - no new campaigns launched

5,102

Leads Post Handover

₹45

CPL Post Handover

4x

Lead Volume Increase

6,352

Total Campaign Leads

56%

CPL Reduction

₹56

Blended CPL

5,102 leads in 9 days. ₹45 CPL. 4x lead volume increase. All delivered without launching a single new campaign or resetting learning phase stability.

The Situation

CREDAI Pune Metro is the Pune chapter of the Confederation of Real Estate Developers Associations of India - one of India's most recognised real estate industry bodies. The campaign was built around a time-sensitive real estate expo event in Pune, requiring a high volume of qualified leads within a fixed and non-negotiable window.

CREDAI Pune Metro was already running Google Ads for their upcoming real estate expo when performance concerns surfaced. They initially approached Digitly for consultation on why the campaign was underdelivering. After reviewing the campaign structure, it became clear that structural inefficiencies - not budget - were limiting delivery and conversion efficiency. The engagement shifted from advisory to full execution.

The constraints were significant. The campaign was already live. Time remaining before the expo was limited. There was no room for a full structural rebuild. And critically - learning phase stability had to be preserved. Resetting the campaign's learning would have cost days the client did not have.

This was not a fresh launch. It was a live performance correction under a deadline.

Campaign already live

Limited time remaining

No full rebuild possible

Learning phase must be preserved

What Our Audit Found

Before Digitly Handover

26 Aug - 7 Sep

1,250

Leads Generated

₹103

Cost Per Lead

Before any changes were made, Digitly conducted a structural audit of the live campaign. Three specific problems were identified - each one silently limiting the campaign's ability to scale.

FINDING 1

Conversion Signal Confusion

Multiple conversion actions had been set as primary optimization goals simultaneously. Google's bidding algorithm was receiving conflicting signals about what the campaign was actually trying to achieve - meaning it could not optimise efficiently for the lead outcome that mattered.

FINDING 2

Account-Level Goal Dilution

Campaigns were optimising against account-level goals rather than campaign-specific objectives. This meant the algorithm was being pulled in multiple directions by signals from across the account - rather than focusing entirely on the specific conversion outcome required for the expo campaign.

FINDING 3

Audience Signal Weakness

High-intent real estate audience signals had not been fully leveraged. The campaign was not targeting the custom segments most closely aligned with real estate browsing and purchase behaviour - meaning impression delivery was reaching a broader, lower-intent audience than the budget should have been funding.

"The issue was not traffic volume. It was structural signal clarity."

The Intervention

The solution required surgical precision. No new campaigns. No aggressive restructuring. No learning reset. Five targeted changes - all implemented within the live campaign framework.

Surgical Optimisation Framework
01

Conversion Signal Cleanup

All secondary conversion actions removed from primary optimisation goals. Only lead form submission retained as the single primary signal. This immediately clarified what the bidding algorithm was being asked to optimise for.

02

Campaign Goal Alignment

Account-level goal optimisation removed. Each campaign reassigned to campaign-specific objectives only - preventing signal dilution from unrelated account activity and allowing the algorithm to focus exclusively on expo lead generation.

03

Audience Reinforcement

High-intent custom audience segments rebuilt and strengthened - specifically aligned with real estate browsing behaviour, property search patterns and expo-relevant intent signals. The campaign began reaching buyers closer to a purchase decision.

04

Channel Prioritisation

Performance Max and Display campaigns leveraged for faster algorithmic learning under the time constraint - allowing the campaign to scale delivery speed without the slower optimisation cycles typical of standard Search campaigns alone.

05

Learning Stability Protected

No new campaigns launched throughout the intervention. All changes implemented within the existing campaign structure to preserve accumulated learning data and avoid triggering a new learning phase that would have cost days of reduced delivery.

The Turnaround

Before (26 Aug - 7 Sep)
1,250 leads in 13 days
₹103 Cost Per Lead
Underdelivering campaign
Signal confusion in bidding
Broad low-intent audiences
After Digitly (8 Sep - 16 Sep)
5,102 leads in 9 days
₹45 Cost Per Lead
4x lead volume increase
56% CPL reduction
Scaled without resetting learning

In 9 days - without launching a single new campaign - lead volume increased 4x and CPL dropped from ₹103 to ₹45. The campaign delivered more leads in the 9-day post-handover window than it had generated in the entire preceding period. Not through more budget. Through structural clarity.

Full Campaign Performance

Across the complete campaign window including both pre and post-handover periods:

Full Campaign Stats

Total Leads Generated6,352
Blended CPL₹56
Total Ad Spend₹3,58,471
Total Impressions2,290,177
Total Clicks95,108

Post-Handover Period (8 Sep - 16 Sep - 9 Days)

Leads Generated5,102
Cost Per Lead₹45
Lead Volume vs Prior4x increase
CPL Improvement56% reduction

Why a 9-Day Intervention Produced a 4x Result.

The result came from one insight - the campaign's underperformance was entirely structural, not a budget problem. Every symptom - low lead volume, high CPL, poor delivery - traced back to the same root cause. The bidding algorithm was receiving contradictory signals about what it was supposed to optimise for. Once those signals were clarified and the audience targeting was strengthened, the algorithm had everything it needed to perform. The budget was always sufficient. The structure was not.

The decision to preserve learning phase stability was the difference between a 9-day rescue and a 9-day reset. Launching new campaigns would have been the instinctive response - but it would have restarted the learning cycle and cost the client the performance ramp-up period they could not afford given the expo deadline. Surgical changes within the existing structure allowed the accumulated learning to compound immediately into stronger delivery from the first day of intervention.

Qualification Over Volume

Signal clarity directly determines how efficiently an algorithm can spend budget. Fix the signals before increasing the spend.

Segmentation Over Guesswork

Audience reinforcement with high-intent real estate segments narrowed delivery to buyers closer to a decision - improving both volume and quality simultaneously.

Structure Over Reaction

No new campaigns. No aggressive changes. Surgical precision within the existing structure produced a 4x result without disruption.

Data Over Assumptions

Every intervention decision was based on what the audit data showed - not what instinct suggested. The data said fix the signals. We fixed the signals.

"Running a live campaign that isn't performing? The problem is almost never the budget. It's almost always the structure."

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